This repository contains the unit proofs as well as a build system used in the Verifying Verified Code case study. Verified Code refers to the aws-c-common library, which is now being verified by CBMC as part of the library's CI process. Read more about the AWS case study that inspired our work here . Instead of CBMC, our case study uses SeaHorn's BMC engine for bounded model checking. We also adopted de facto semantics in the proofs and specifications, which allows this build system to use the same set of unit proofs for different verification tools and techniques. In specific, we enabled symbolic execution with KLEE and fuzzing with libFuzzer. NOTE: The recommended version of LLVM for KLEE is LLVM-11 (with added support for 12 and 13) Make sure to use the correct version of LLVM and seahorn when using KLEE seahorn for LLVM-11: https://github.com/seahorn/seahorn/tree/dev11
Detailed analysis of run-times is available in an accompanying Jupyter Notebook in Google Colab. Coverage reports from fuzzing are available here.
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Siddharth Priya, Xiang Zhou, Yusen Su, Yakir Vizel, Yuyan Bao, Arie Gurfinkel: Verifying Verified Code. The 19th International Symposium on Automated Technology for Verification and Analysis (ATVA 2021) (ArXiv) (Video)
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Siddharth Priya, Xiang Zhou, Yusen Su, Yakir Vizel, Yuyan Bao, Arie Gurfinkel: Bounded Model Checking for LLVM. The 22nd International Conference on Formal Methods in Computer-Aided Design (FMCAD 2022).
Below is the high level architecture graph of our case study.
A unit proof is a small piece of code (usually main function only) that verifies a function by doing the following:
- assumes pre-conditions regarding the function and data structure
- invokes a function under verification
- asserts post-conditions regarding the function and data structure
Unit proofs are organized under verification jobs. A job with NAME is placed under the directory seahorn/jobs/NAME/
. A job directory contains a unit proof c file, CMakeLists.txt
for CMake and an optional sea.yaml
file containing job-specific configurations. An example unit proof for job array_eq
has the unit proof aws_array_eq_harness.c
.
The proof library contains helper functions that improves the expressiveness, efficiency and standardization of unit proofs. Examples include initialization functions for data structures and functions for expressing complex post-conditions. The proof library is located under seahorn/include/
and seahorn/lib/
.
To make verification scalable, the verification of method A that calls another method B may use a specification stub that approximates the functionality of B. We implemented these stub functions under seahorn/aws-c-common-stubs/
.
The tool-specific builds for SeaHorn, KLEE and libFuzzer are containerized with docker for CI. You can also build these containers locally to replicate the verification results.
Dockerfile: docker/verify-c-common.Dockerfile
.
To build and run all seahorn verification jobs:
$ docker build -t verify-c-common . --file docker/verify-c-common.Dockerfile
$ docker run -t verify-c-common /bin/bash -c "cd build && mkdir -p /tmp/verify-c-common && env VERIFY_FLAGS=\"<FLAGS>\" ctest -j<THREAD_NUM> --output-on-failure --timeout 2000"
Set <FLAGS>
to a space delimited string to specify flags for every verification job. For example set <FLAGS>
to --cex --horn-bmc-solver=smt-y2
will run every job under counter example mode and use Yices 2 as the SMT solver instead of z3. More details on verification options can be found in a later section. Set <THREAD_NUM>
to a number suitable for your machine to run verification jobs in parallel.
Dockerfile: docker/verify-c-common-smack.Dockerfile
.
To build and run all SMACK jobs:
$ docker build -t verify-c-common:smack . --file docker/verify-c-common-smack.Dockerfile
$ docker run -t verify-c-common:smack /bin/bash -c "cd build && ctest -R smack_ --timeout 2000"
Dockerfile: docker/verify-c-common-symbiotic.Dockerfile
.
To build and run all Symbiotic jobs:
$ docker build -t verify-c-common:symbiotic . --file docker/verify-c-common-symbiotic.Dockerfile
$ docker run -t verify-c-common:symbiotic /bin/bash -c "cd build && ctest -R symbiotic_ --timeout 5000"
Dockerfile: docker/verify-c-common-klee.Dockerfile
.
To build and run all KLEE jobs:
$ docker build -t verify-c-common:klee . --file docker/verify-c-common-klee.Dockerfile
$ docker run -t verify-c-common:klee /bin/bash -c "cd build && ctest -R klee_ --timeout 2000"
Dockerfile: docker/verify-c-common-fuzz.Dockerfile
.
To build and run all libFuzzer jobs:
$ docker build -t verify-c-common:fuzz . --file docker/verify-c-common-fuzz.Dockerfile
$ docker run -t verify-c-common:fuzz /bin/bash -c "cd build && ctest -R fuzz_ --timeout 2000"
Dockerfile: docker/aws-c-common.Dockerfile
.
To build and run all aws-c-common jobs by cbmc:
$ docker build -t aws-c-common:latest . --file docker/aws-c-common.Dockerfile
$ docker run -t aws-c-common:latest /bin/bash -c "cd scripts && python3 run_aws_res.py"
Note that, it will copy a python script run_aws_res.py
under the scripts
folder in the container.
This is a common step for all other configurations.
-
Clone aws-c-common project in the root directory of the project so that a sub-directory
aws-c-common
is created$ git clone https://github.com/awslabs/aws-c-common
-
Configure
aws-c-common
as instructed, make sure to compile withclang-14
so that fuzzing can work. Configure using the following commands:$ cd aws-c-common $ mkdir build $ cd build $ cmake \ -DCMAKE_C_COMPILER=clang-14 \ -DCMAKE_EXPORT_COMPILE_COMMANDS=1 \ -DCMAKE_INSTALL_PREFIX=$(pwd)/run ../ -GNinja
-
Build
aws-c-common
library:$ cmake --build . --target install
or
$ ninja install
As a prerequisite, follow this guide to build SeaHorn locally.
-
Create a build directory
$ mkdir build ; cd build
-
Configure with cmake
$ cmake \ -DSEA_LINK=llvm-link-14 \ -DCMAKE_C_COMPILER=clang-14 \ -DCMAKE_CXX_COMPILER=clang++-14 \ -DSEAHORN_ROOT=<SEAHORN_ROOT> \ -Daws-c-common_DIR=<AWS_C_COMMON_CMAKE_DIR> ../ -GNinja
SEAHORN_ROOT
is the directory containing your local SeaHorn repository.AWS_C_COMMON_CMAKE_DIR
is the directory underaws-c-common
project containing the fileaws-c-common-config.cmake
.This will also allow the project to be configured and compiled within VS Code using the CMake Tools extension.
Alternatively, the project can be configured using cmake presets. To do this, simply run the following command:
$ cmake --preset <PRESET_NAME>
Where
PRESET_NAME
is the preset you would like to use. The presets that are currently available are:default-jammy
. These presets assume thatverify-c-common
andseahorn
are in your home directory and thataws-c-common
is in yourverify-c-common
directory.This will also allow the project to be configured and compiled within VS Code using the CMake Tools extension.
If you would like to use different compilation settings or if you have
verify-c-common
,aws-c-common
orseahorn
in any other directory, you will need to make your ownCMakeUserPresets.json
file with your own presets. -
Compile
$ ninja
or
$ cmake --build .
Compiled bitcode files are placed under build/seahorn/jobs/<NAME>/llvm-ir/<NAME>.bc
- Verify
or
$ ninja test
or$ cmake --build . --target test
$ ctest
- Run individual test
$ ctest -R <TEST_NAME>
- Run individual file manually
$ ./verify [options] <BC_FILE_NAME>
--cex
: runs verification under counterexample(cex) mode. Cex mode changes configuration options
to yield more readable results if the result is SAT
(one of the assertions failed). A counterexample harness file will also be generated at /tmp/h.ll
. You can link the harness file with unit proof bitcode file with $SEA cex
to create an executable counterexample:
$SEA cex -m64 -g --only-strip-extern --keep-lib-fn --klee-internalize <BC_FILE_NAME> /tmp/h.ll -o debug
. Running in cex mode might negatively affect the verification
time, but could be very useful for debugging.
--vac
: runs verification under vacuity(vac) mode. Vac mode checks whether any of the assertions are vacuously true, in other words whether any assertions are not reachable. It is recommended to always run verification jobs under vac mode when a new job returns UNSAT
to check whether it is a false positive.
--horn-bmc-solver=[smt-z3, smt-y2]
: chooses the smt-solver that will be used for BMC verification. Z3 is used by default; set this flag to smt-y2
to choose Yices2 instead. Yices2 can sometimes yield a much shorter verification time under cex mode.
Leave aws-c-common
library as is if you have already built verification jobs for SeaHorn.
As a prerequisite, build SMACK following this guide. Note, we require to use LLVM 12.0.1. The last commit that SMACK supports LLVM 12 is 4894245.
NOTE: The recommended version of LLVM for SMACK is LLVM-12 Make sure to use the correct version of LLVM and seahorn when using SMACK seahorn for LLVM-12: https://github.com/seahorn/seahorn/tree/dev12
Enter the verification build directory and reconfigure CMake to enable SMACK:
$ cmake \
-DSEA_LINK=llvm-link-12 \
-DCMAKE_C_COMPILER=clang-12 \
-DCMAKE_CXX_COMPILER=clang++-12 \
-DSEAHORN_ROOT=<SEAHORN_ROOT> \
-DSEA_ENABLE_SMACK=ON \
-Daws-c-common_DIR=<AWS_C_COMMON_CMAKE_DIR> \
../ -GNinja
Rebuild with:
$ cmake --build .
or
$ ninja
To run all SMACK tests:
$ ctest -R smack_
To run a individual test for job with NAME
, find SMACK specific LLVM assembly file under seahorn/jobs/NAME/llvm-ir/NAME.smack.ir/NAME.smack.ir.ll
.
Run with your local SMACK executable:
$ smack --check assertions --time-limit 300 --no-memory-splitting \
--integer-encoding unbounded-integer --pointer-encoding unbounded-integer \
seahorn/jobs/${NAME}/llvm-ir/${NAME}.smack.ir/${NAME}.smack.ir.bc
We have adapted SMACK by using different configurations supported by the tool, including options for ineger / pointer encoding, options for property checks, and options for its memory model. The shown one is the configuration which SMACK performs best as we collected. All verification results by giving different options we collected and reasoning on a jupyter notebook.
Leave aws-c-common
library as is if you have already built verification jobs for SeaHorn.
NOTE: The recommended version of LLVM for Symbiotic is LLVM-10 Make sure to use the correct version of LLVM and seahorn when using Symbiotic seahorn for LLVM-10: https://github.com/seahorn/seahorn/tree/dev10
As a prerequisite, build Symbiotic following this guide. Note, we require to use LLVM 10.0.1.
Enter the verification build directory and reconfigure CMake to enable Symbiotic:
$ cmake \
-DSEA_LINK=llvm-link-10 \
-DCMAKE_C_COMPILER=clang-10 \
-DCMAKE_CXX_COMPILER=clang++-10 \
-DSEAHORN_ROOT=<SEAHORN_ROOT> \
-DSEA_ENABLE_SYMBIOTIC=ON \
-Daws-c-common_DIR=<AWS_C_COMMON_CMAKE_DIR> \
../ -GNinja
Rebuild with:
$ cmake --build .
or
$ ninja
To run all Symbiotic tests:
$ ctest -R symbiotic_
Note, the CTest does not report error properly for Symbiotic. The verification result for Symbiotic should strictly follow the outputs of the tool.
To run a individual test for job with NAME
, find Symbiotic specific BC file under seahorn/jobs/NAME/llvm-ir/NAME.symbiotic.ir/NAME.symbiotic.ir.bc
.
Run with your local Symbiotic executable:
$ symbiotic --replay-error --report=short --prp=assert seahorn/jobs/${NAME}/llvm-ir/${NAME}.symbiotic.ir/${NAME}.symbiotic.ir.bc
We reasoned why Symbiotic can take less times on verifying priority_queue
and ring_buffer
categories where other tools may take longer. We tried to add some failed assertions like sassert(false)
(aka. __VERIFIER_assert(false)
) on the proofs such as priority_queue_push
, priority_queue_push_ref
, and priority_queue_s_swap
. However, Symbiotic still report no error found on all those cases. The details can be found on issue 124.
Leave aws-c-common
library as is if you have already built verification jobs for SeaHorn.
As a prerequisite, build KLEE following this guide. Note, we require to use LLVM 11.1.0.
NOTE: The recommended version of LLVM for KLEE is LLVM-11 (with added support for 12 and 13) Make sure to use the correct version of LLVM and seahorn when using KLEE seahorn for LLVM-11: https://github.com/seahorn/seahorn/tree/dev11
Enter the verification build directory and reconfigure CMake to enable KLEE:
$ cmake \
-DSEA_LINK=llvm-link-11 \
-DCMAKE_C_COMPILER=clang-11 \
-DCMAKE_CXX_COMPILER=clang++-11 \
-DSEAHORN_ROOT=<SEAHORN_ROOT> \
-DSEA_ENABLE_KLEE=ON \
-Daws-c-common_DIR=<AWS_C_COMMON_CMAKE_DIR> \
../ -GNinja
Rebuild with:
$ cmake --build .
or
$ ninja
To run all KLEE tests:
$ ctest -R klee_
To run a individual test for job with NAME
, find KLEE specific BC file under seahorn/jobs/NAME/llvm-ir/NAME.klee.ir/NAME.klee.ir.bc
.
Run with your local KLEE executable:
$ klee --libc=uclibc --exit-on-error seahorn/jobs/${NAME}/llvm-ir/${NAME}.klee.ir/${NAME}.klee.ir.bc
As a prerequisite, install the following tools: llvm-14 llvm-14-dev llvm-14-tools lcov
.
We need to rebuild aws-c-common
with fuzzing and coverage cflags.
Reconfigure:
$ cd aws-common/build/
$ cmake -DCMAKE_C_COMPILER=clang-14 \
-DCMAKE_EXPORT_COMPILE_COMMANDS=1 \
-DCMAKE_INSTALL_PREFIX=$(pwd)/run \
-DCMAKE_C_FLAGS='-fsanitize=fuzzer-no-link,address,undefined -fprofile-instr-generate -fcoverage-mapping' \
../ -GNinja
Rebuild:
$ cmake --build . --target install
or
$ ninja install
Enter the verification build directory and reconfigure CMake to enable fuzzing:
$ cmake \
-DSEA_LINK=llvm-link-14 \
-DCMAKE_C_COMPILER=clang-14 \
-DCMAKE_CXX_COMPILER=clang++-14 \
-DSEAHORN_ROOT=<SEAHORN_ROOT> \
-DSEA_ENABLE_FUZZ=ON \
-Daws-c-common_DIR=<AWS_C_COMMON_CMAKE_DIR> \
../ -GNinja
Rebuild with:
$ cmake --build .
or
$ ninja
To run all libFuzzer tests:
$ ctest -R fuzz_
The fuzzing target executable for verification job <NAME>
is installed as build/seahorn/jobs/<NAME>/<NAME>_fuzz
. build/seahorn/jobs/<NAME>/corpus/
will contain some corpus inputs generated by libFuzzer if any fuzzing runs are executed.
$ build/seahorn/jobs/<NAME>/<NAME>_fuzz -h
will show you all the options for libFuzzer.
To fuzz individual targets, run
$ ASAN_OPTIONS=detect_leaks=0 build/seahorn/jobs/<NAME>/<NAME>_fuzz corpus -use_value_profile=1 -detect_leaks=0 -runs=<RUN_NUM> -allocator_may_return_null=1
This command will fuzz the target for at most <RUN_NUM>
times or until a crash has occurred. Memory leak detection is turned off to prevent spurious memory leak warnings.
We configured libFuzzer to output source-based coverage data. Once a target has been fuzzed for the desired number of times, build/seahorn/jobs/<NAME>/corpus/
will contain some corpus input files. Running the fuzzing target again with --runs=0
will make libFuzzer run the target with existing corpus files only and output coverage data.
$ ASAN_OPTIONS=detect_leaks=0 build/seahorn/jobs/<NAME>/<NAME>_fuzz corpus -detect_leaks=0 -runs=0
Now build/seahorn/jobs/<NAME>/
should contain a profile data file named default.profraw
containing coverage data.
After running all fuzzing tests, run scripts/get_fuzzing_coverage.py
to output trace files of all source files under data/fuzz_coverage/
. The file is readable and optionally by lcov
. The script also supports generating HTML reports with the flag --html-dir
.
$ python3 scripts/get_fuzzing_coverage.py --build-dir=<BUILD_DIR> --html-dir=<HTML_DIR>